IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i15p3945-d393223.html
   My bibliography  Save this article

The Value of PV Power Forecast and the Paradox of the “Single Pricing” Scheme: The Italian Case Study

Author

Listed:
  • Marco Pierro

    (Department of Enterprise Engineering, University of Rome Tor Vergata, 00133 Rome, Italy
    EURAC Research, Institute for Renewable Energy, Viale Druso, 1, 39100 Bolzano, Italy)

  • David Moser

    (EURAC Research, Institute for Renewable Energy, Viale Druso, 1, 39100 Bolzano, Italy)

  • Richard Perez

    (Atmospheric Sciences Research Center, State University of New York, Albany, NY 12203, USA)

  • Cristina Cornaro

    (Department of Enterprise Engineering, University of Rome Tor Vergata, 00133 Rome, Italy
    CHOSE, University of Rome Tor Vergata, 00133 Rome, Italy)

Abstract

One of the major problem of photovoltaic grid integration is limiting the solar-induced imbalances since these can undermine the security and stability of the electrical system. Improving the forecast accuracy of photovoltaic generation is becoming essential to allow a massive solar penetration. In particular, improving the forecast accuracy of large solar farms’ generation is important both for the producers/traders to minimize the imbalance costs and for the transmission system operators to ensure stability. In this article, we provide a benchmark for the day-ahead forecast accuracy of utility scale photovoltaic (PV) plants in 1325 locations spanning the country of Italy. We then use these benchmarked forecasts and real energy prices to compute the economic value of the forecast accuracy and accuracy improvement in the context of the Italian energy market’s regulatory framework. Through this study, we further point out several important criticisms of the Italian “single pricing” system that brings paradoxical and counterproductive effects regarding the need to reduce the imbalance volumes. Finally, we propose a new market-pricing rule and innovative actions to overcome the undesired effects of the current dispatching regulations.

Suggested Citation

  • Marco Pierro & David Moser & Richard Perez & Cristina Cornaro, 2020. "The Value of PV Power Forecast and the Paradox of the “Single Pricing” Scheme: The Italian Case Study," Energies, MDPI, vol. 13(15), pages 1-27, August.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:15:p:3945-:d:393223
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/15/3945/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/15/3945/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Pierro, Marco & De Felice, Matteo & Maggioni, Enrico & Moser, David & Perotto, Alessandro & Spada, Francesco & Cornaro, Cristina, 2020. "Residual load probabilistic forecast for reserve assessment: A real case study," Renewable Energy, Elsevier, vol. 149(C), pages 508-522.
    2. Kaur, Amanpreet & Nonnenmacher, Lukas & Pedro, Hugo T.C. & Coimbra, Carlos F.M., 2016. "Benefits of solar forecasting for energy imbalance markets," Renewable Energy, Elsevier, vol. 86(C), pages 819-830.
    3. Wu, Jing & Botterud, Audun & Mills, Andrew & Zhou, Zhi & Hodge, Bri-Mathias & Heaney, Mike, 2015. "Integrating solar PV (photovoltaics) in utility system operations: Analytical framework and Arizona case study," Energy, Elsevier, vol. 85(C), pages 1-9.
    4. Clò, Stefano & Fumagalli, Elena, 2019. "The effect of price regulation on energy imbalances: A Difference in Differences design," Energy Economics, Elsevier, vol. 81(C), pages 754-764.
    5. Pierro, Marco & Perez, Richard & Perez, Marc & Moser, David & Cornaro, Cristina, 2020. "Italian protocol for massive solar integration: Imbalance mitigation strategies," Renewable Energy, Elsevier, vol. 153(C), pages 725-739.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ángel A. Bayod-Rújula & Juan A. Tejero-Gómez, 2022. "Analysis of the Hybridization of PV Plants with a BESS for Annual Constant Power Operation," Energies, MDPI, vol. 15(23), pages 1-18, November.
    2. Miguel López Santos & Xela García-Santiago & Fernando Echevarría Camarero & Gonzalo Blázquez Gil & Pablo Carrasco Ortega, 2022. "Application of Temporal Fusion Transformer for Day-Ahead PV Power Forecasting," Energies, MDPI, vol. 15(14), pages 1-22, July.
    3. Pierro, Marco & Perez, Richard & Perez, Marc & Moser, David & Cornaro, Cristina, 2021. "Imbalance mitigation strategy via flexible PV ancillary services: The Italian case study," Renewable Energy, Elsevier, vol. 179(C), pages 1694-1705.
    4. Hassan Elahi & Khushboo Munir & Marco Eugeni & Sofiane Atek & Paolo Gaudenzi, 2020. "Energy Harvesting towards Self-Powered IoT Devices," Energies, MDPI, vol. 13(21), pages 1-31, October.
    5. Ludwik Wicki & Robert Pietrzykowski & Dariusz Kusz, 2022. "Factors Determining the Development of Prosumer Photovoltaic Installations in Poland," Energies, MDPI, vol. 15(16), pages 1-19, August.
    6. Abeer Abdullah Al Anazi & Abdullah Albaker & Wongchai Anupong & Abdul Rab Asary & Rajabov Sherzod Umurzoqovich & Iskandar Muda & Rosario Mireya Romero-Parra & Reza Alayi & Laveet Kumar, 2022. "Technical, Economic, and Environmental Analysis and Comparison of Different Scenarios for the Grid-Connected PV Power Plant," Sustainability, MDPI, vol. 14(24), pages 1-16, December.
    7. Avesani, Diego & Zanfei, Ariele & Di Marco, Nicola & Galletti, Andrea & Ravazzolo, Francesco & Righetti, Maurizio & Majone, Bruno, 2022. "Short-term hydropower optimization driven by innovative time-adapting econometric model," Applied Energy, Elsevier, vol. 310(C).
    8. Marco Pierro & Fabio Romano Liolli & Damiano Gentili & Marcello Petitta & Richard Perez & David Moser & Cristina Cornaro, 2022. "Impact of PV/Wind Forecast Accuracy and National Transmission Grid Reinforcement on the Italian Electric System," Energies, MDPI, vol. 15(23), pages 1-28, November.
    9. Mayer, Martin János, 2022. "Impact of the tilt angle, inverter sizing factor and row spacing on the photovoltaic power forecast accuracy," Applied Energy, Elsevier, vol. 323(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gandhi, Oktoviano & Zhang, Wenjie & Kumar, Dhivya Sampath & Rodríguez-Gallegos, Carlos D. & Yagli, Gokhan Mert & Yang, Dazhi & Reindl, Thomas & Srinivasan, Dipti, 2024. "The value of solar forecasts and the cost of their errors: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    2. Pierro, Marco & Perez, Richard & Perez, Marc & Moser, David & Cornaro, Cristina, 2021. "Imbalance mitigation strategy via flexible PV ancillary services: The Italian case study," Renewable Energy, Elsevier, vol. 179(C), pages 1694-1705.
    3. Pierro, Marco & Perez, Richard & Perez, Marc & Prina, Matteo Giacomo & Moser, David & Cornaro, Cristina, 2021. "Italian protocol for massive solar integration: From solar imbalance regulation to firm 24/365 solar generation," Renewable Energy, Elsevier, vol. 169(C), pages 425-436.
    4. Pierro, Marco & De Felice, Matteo & Maggioni, Enrico & Moser, David & Perotto, Alessandro & Spada, Francesco & Cornaro, Cristina, 2020. "Residual load probabilistic forecast for reserve assessment: A real case study," Renewable Energy, Elsevier, vol. 149(C), pages 508-522.
    5. Marco Pierro & Fabio Romano Liolli & Damiano Gentili & Marcello Petitta & Richard Perez & David Moser & Cristina Cornaro, 2022. "Impact of PV/Wind Forecast Accuracy and National Transmission Grid Reinforcement on the Italian Electric System," Energies, MDPI, vol. 15(23), pages 1-28, November.
    6. Kaur, Amanpreet & Nonnenmacher, Lukas & Coimbra, Carlos F.M., 2016. "Net load forecasting for high renewable energy penetration grids," Energy, Elsevier, vol. 114(C), pages 1073-1084.
    7. Hu, Jiaxiang & Hu, Weihao & Cao, Di & Sun, Xinwu & Chen, Jianjun & Huang, Yuehui & Chen, Zhe & Blaabjerg, Frede, 2024. "Probabilistic net load forecasting based on transformer network and Gaussian process-enabled residual modeling learning method," Renewable Energy, Elsevier, vol. 225(C).
    8. Jenkins, J.D. & Zhou, Z. & Ponciroli, R. & Vilim, R.B. & Ganda, F. & de Sisternes, F. & Botterud, A., 2018. "The benefits of nuclear flexibility in power system operations with renewable energy," Applied Energy, Elsevier, vol. 222(C), pages 872-884.
    9. Kovacic, Zora & Giampietro, Mario, 2015. "Empty promises or promising futures? The case of smart grids," Energy, Elsevier, vol. 93(P1), pages 67-74.
    10. Sanzana Tabassum & Tanvin Rahman & Ashraf Ul Islam & Sumayya Rahman & Debopriya Roy Dipta & Shidhartho Roy & Naeem Mohammad & Nafiu Nawar & Eklas Hossain, 2021. "Solar Energy in the United States: Development, Challenges and Future Prospects," Energies, MDPI, vol. 14(23), pages 1-65, December.
    11. Elsinga, Boudewijn & van Sark, Wilfried G.J.H.M., 2017. "Short-term peer-to-peer solar forecasting in a network of photovoltaic systems," Applied Energy, Elsevier, vol. 206(C), pages 1464-1483.
    12. Paletta, Quentin & Arbod, Guillaume & Lasenby, Joan, 2023. "Omnivision forecasting: Combining satellite and sky images for improved deterministic and probabilistic intra-hour solar energy predictions," Applied Energy, Elsevier, vol. 336(C).
    13. Jayesh Thaker & Robert Höller, 2023. "Evaluation of High Resolution WRF Solar," Energies, MDPI, vol. 16(8), pages 1-13, April.
    14. Yang, Dazhi & van der Meer, Dennis, 2021. "Post-processing in solar forecasting: Ten overarching thinking tools," Renewable and Sustainable Energy Reviews, Elsevier, vol. 140(C).
    15. Munoz, Francisco D. & Pumarino, Bruno J. & Salas, Ignacio A., 2017. "Aiming low and achieving it: A long-term analysis of a renewable policy in Chile," Energy Economics, Elsevier, vol. 65(C), pages 304-314.
    16. Alessandro Niccolai & Seyedamir Orooji & Andrea Matteri & Emanuele Ogliari & Sonia Leva, 2022. "Irradiance Nowcasting by Means of Deep-Learning Analysis of Infrared Images," Forecasting, MDPI, vol. 4(1), pages 1-11, March.
    17. Gu, Jiafeng, 2023. "Energy poverty and government subsidies in China," Energy Policy, Elsevier, vol. 180(C).
    18. Wang, Wei & Zhang, Yue-Jun, 2022. "Does China's carbon emissions trading scheme affect the market power of high-carbon enterprises?," Energy Economics, Elsevier, vol. 108(C).
    19. Castillejo-Cuberos, A. & Cardemil, J.M. & Escobar, R., 2023. "Techno-economic assessment of photovoltaic plants considering high temporal resolution and non-linear dynamics of battery storage," Applied Energy, Elsevier, vol. 334(C).
    20. Visser, Lennard & AlSkaif, Tarek & van Sark, Wilfried, 2022. "Operational day-ahead solar power forecasting for aggregated PV systems with a varying spatial distribution," Renewable Energy, Elsevier, vol. 183(C), pages 267-282.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:13:y:2020:i:15:p:3945-:d:393223. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.